Cocrystals of Praziquantel: discovery by network-based link prediction

Jan-Joris Devogelaer, Maxime D. Charpentier, Arnoud Tijink, Valerie Dupray, Gérard Coquerel, Karen Johnston, Hugo Meekes, Paul Tinnemans, Elias Vlieg, Joop H. ter Horst, René de Gelder

Research output: Contribution to journalArticlepeer-review

21 Citations (Scopus)
31 Downloads (Pure)


Cocrystallization has been promoted as an attractive early development tool as it can change the physicochemical properties of a target compound and possibly enable the purification of single enantiomers from racemic compounds. In general, the identification of adequate cocrystallization candidates (or coformers) is troublesome and hampers the exploration of the solid-state landscape. For this reason, several computational tools have been introduced over the last two decades. In this study, cocrystals of Praziquantel (PZQ), an anthelmintic drug used to treat schistosomiasis, are predicted with network-based link prediction and experimentally explored. Single crystals of 12 experimental cocrystal indications were grown and subjected to a structural analysis with single-crystal X-ray diffraction. This case study illustrates the power of the link-prediction approach and its ability to suggest a diverse set of new coformer candidates for a target compound when starting from only a limited number of known cocrystals.
Original languageEnglish
Pages (from-to)3428-3437
Number of pages10
JournalCrystal Growth and Design
Issue number6
Early online date20 May 2021
Publication statusPublished - 2 Jun 2021


  • cocrystallization
  • Praziquantel
  • biopharmaceutics classification system


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